In the avian embryo, cardiac progenitor fields fuse to form a tubular heart at the midline. Subsequently, this tube undergoes a process of flexion and rotation;resulting in a looped heart. Our long-term goal is to determine if multiple genetic and signaling defects converge at a common mechanical nexus to prevent proper heart morphogenesis. It is known that local cell- extracellular matrix (ECM) interactions are critical for early heart development. In addition, we propose that global tissue deformations directly influence cell motion and the ongoing reorganization of the ECM necessary for proper heart tube formation and looping. Accordingly, the following hypotheses will be tested: First, that cells and ECM components required for heart morphogenesis are recruited from distant sites;Second, that tissue-level (convective) events are involved in the displacement of these raw materials;Third, that proper heart morphogenesis requires ongoing tissue-level reorganization of cell collectives and the recruited ECM fibrils;and Fourth, that perturbations to the mechanical micro-environment, such as disruption of local tension fields or cell-ECM interactions, will cause reproducible heart malformations. Accordingly, we will: 1) Determine mesodermal cell and ECM fibril position-fate maps during avian tubular heart formation in normal and experimentally perturbed embryos;2) Compute the component of total cell displacements attributable to local autonomous cell displacements versus tissue convection;3) Compute strain in the heart-forming regions of normal and experimentally perturbed embryos;and 4) Construct a predictive finite element model encompassing tubular heart morphogenesis. These aims will be accomplished using DIC and epifluorescence time lapse microscopy and subsequent computational analyses of the resulting image frames. PUBLIC HEALTH RELEVANCE In vivo time-lapse imaging and computational analyses will define the motion patterns of cells and ECM fibrils during early heart formation. Relating motion data to deformation data will provide insights into the importance of mechanical patterning during heart morphogenesis, which is the result of multiple genetic signaling events. Predictive computer models will characterize the bio-mechanics of heart malformations and provide useful information to help prevent related heart defects.